Mobile Robot Control Based on Boolean Logic with Internal Memory

摘要

The purpose of this paper is to explore the effect of adding known amounts of memory to pure reactive systems in a variety of tasks. Using a finite state machine approach, we construct controllers for a simulated robot for five tasks―obstacle avoidance, wall following, exploration, and box pushing―with two sensor configurations using evolutionary computation techniques, and compare the performance of stateless and memory-based controllers. For obstacle avoidance and exploration no significant difference is observed; for wall-following and box pushing, stateless controllers are significantly worse than memory-based but increasing amounts of memory give no significant increase in performance. The need for memory in these cases reflects a need to discriminate sen-sorimotor contexts to effectively perform the task.